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THE METHOD OF HYBRID FUNCTIONS FOR THE NUMERICAL SOLUTION OF THE HODGKIN-HUXLEY MODEL

IFAC-PapersOnLine 2022年第1期55卷 623-630页

作者： Anindita Ganguly Manika Saha Aniruddha Ghosh Ursa Maity Jan P. Kucera Soumyendu Raha Department of Computational and Data Sciences Indian Institute of Science Bangaluru 5600012 India Department of Robotics and Automation Sister Nivedita University Kolkata700150 India Department of Electrical Engineering Indian Institute of Technology Dhanbad India School of Biomedical Engineering University of British Columbia Vancouver Canada Department of Physiology University of Bern Bern Switzerland

Background and objective: The Hodgkin-Huxley framework of equations represent the generation of the nerve action potential. It is a fairly complex biophysical model that is non-linear in nature. It has four sets of coupled differential equations representing the membrane voltage and the gate variables. The conventional way of solving such systems is usually the forward Euler method. Some other computational methods are the Rush-Larsen (RL) method and, Runge-Kutta (RK) methods. In MATLAB, a popular method used is the ODE45 solver, which is actually 4 th order Runge Kutta method. Method: In this paper, a new and simplified computational method is proposed which is called the Hybrid Functions (HF) method. To solve these differential equations representing a complex biological model, we present a detailed derivation of the proposed algorithm. Results: A detailed comparative study based on computational speed, absolute error and Integral Timed Squared Error (ITSE) was then conducted on the aforementioned algorithms. Conclusion: The results show that, due to the simplification of steps because of approximations considered in solving the system of equations, the HF method is quite effective for computing solutions of complex biophysical models with ease.

关键词： Hodgkin-Huxley model Hybrid function Biophysical model Numerical methods Membrane potential

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Faulty diagnostics model for wind power plant application using AI

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Measurement: Sensors 2023年 25卷

作者： Sudhakar, Puladasu Kamble, Nitin K. K, Geetha Turukmane, Anil V. Perli, Suresh Babu P, Jayaraman Department of Electrical and Electronics Engineering Sree Visvesvaraya Institute of Technology and Science Telangana Mahabubnagar509204 India Department of Robotics and Automation D. Y. Patil College of Engineering Pradhikaran Akurdi Pune411044 India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Chengalpattu District Kattankulathur603203 India Department of Computer Science & Engineering VIT- AP University AmaravatiVijaywada India Department of Electrical Engineering NIT Warangal Telangana WARANGAL506004 India Department of Mechanical Engineering Prathyusha Engineering College Aranvoyalkuppam Tiruvallur Tamil Nadu Chennai602025 India

Researchers desperately ought to build an efficient turbine problem detection & simulation environment given the quick increase in wind energy capacity and the steadily rising operational cost duration of wind generators. The two aspects of fault identification & fault prediction are employed to describe the primary problem features of wind generators. We examine and synthesize the studies on fault detection techniques that rely on vibrating, electrical impulse evaluation, and pattern matching to address the challenging difficulties of defect detection. During the same period, we highlight the computationally efficient, constraints, and potential directions of distinct approaches. We review recent study developments & suggest a defect forecasting model that utilizes a physical breakdown prototype with data analysis theory fused depending on the mechanics and electronic subsystem degradation features of wind energy. In this study, we employ the Internet of Things (IoT) on Deep Learning (DL) architecture to forecast and identify wind energy generation issues. The testing findings demonstrate the method's ability to diagnose faults logically and forecast their types. © 2022 The Authors

关键词： Pattern matching

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Underwater Soft Gripper Hydraulic Drive Control System Based on Rigid-flexible Coupling Accumulator

Underwater Soft Gripper Hydraulic Drive Control System Based...

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Chinese automation Congress (CAC)

作者： Li Bai Daohui Zhang Xin Fu Liyan Mo Yunfei Bai Qifeng Zhang Xingang Zhao The State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Department of Information Science and Engineering Northeastern University Shenyang China

Underwater manipulators are critical in the development of marine resources. Traditional rigid manipulators cannot be applied for underwater operations requiring non-destructive grasping, such as biological sampling and artifact salvage, due to their large size and dimensions and complex force feedback control. Soft robotics underwater manipulators overcome this challenge by providing a dexterous and lightweight arm and gripper, but still require high power drive elements and high-frequency valve control components to achieve the required dynamic performance. In this work, we propose a rigid-flexible coupling accumulator that takes into account the lightweight characteristics of the flexible accumulator and the strong energy storage characteristics of the rigid accumulator, starting from the high-power drive unit. On this basis, we propose a hydraulic drive control system based on the rigid-flexible coupling accumulator for the submerged soft gripper. The system can achieve depth self-adaptation and a fast and stable drive for different volumes of the soft gripper, facilitating the application of soft grippers in marine resource exploitation. The proposed design method and analytical model of the rigid-flexible accumulator can also be used as a guide for other applications.

关键词： Couplings Performance evaluation Analytical models Hydraulic drives Dynamics Grasping Control systems

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Design of a Novel Modular Flux Switching Permanent Magnet Resolver

Design of a Novel Modular Flux Switching Permanent Magnet Re...

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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Wenyuan Mi Jincheng Yu Zaixin Song Kuang Yang Zheng Cai Hang Zhao School of Mechanical Engineering and Automation Harbin Institute of Technology (Shenzhen) Shenzhen China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong SAR China Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

Permanent magnet (PM) resolvers are highly employed with the ascent of the electric machine speed. In this digest, a novel modular flux switching PM (FSPM) resolver is designed based on the FSPM machine. By removing the stator yoke, the flux path in each tooth coil is fixed and the total harmonic distortion (THD) of the output voltage is reduced to only 0.37%. Moreover, the proposed 12/16 FSPM resolver can be adapted to fit different rotor poles under the same mechanical support with different modular units (e.g., 6/8 and 10/8 FSPM resolver). Therefore, it can be applied in electric machines with variable rotor pole pairs.

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A Hollow FBG-Based 3-Axis Force Sensor for Surgical Robots

A Hollow FBG-Based 3-Axis Force Sensor for Surgical Robots

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Jie Li Weiquan Deng Chongyang Wang Haoning Cheng Junlin Cui Ming Liang Hao Liu School of Mechanical Engineering Shenyang Jianzhu University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Minimally Invasive Surgical Robot Shenyang China Department of Cardiology the General Hospital of Northern Theater Command of the Chinese People's Liberation Army

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

The ability to perceive forces is crucial for surgical robots to perform operations safely and achieve effective treatment. This paper presents the design of a hollow force sensor based on fiber Bragg gratings (FBGs) to detect 3-Axis forces between the instrument and tissue. The sensor, consisting of an elastic body and four optical fibers with FBGs, is designed for convenient integration into instruments. Unlike most previous force sensors proposed by researchers, which fail to balance sensitivity across axes and have a hollow structure, the sensor designed in this paper positions the optical fibers away from the center to reserve sufficient space for the instrument channel. Additionally, the proposed elastic body comprises both an outer tube of flexible deformable beams and inner support pillars that enhance radial stiffness. This design ensures sensitivity along the axis while increasing stiffness against bending deformation radially. Furthermore, the force sensor is manufactured using 3D printing, making assembly simple and enabling easy interchangeability of instrument tips for various surgical instruments. Finite element simulations and experiments were conducted to verify the sensor’s excellent linearity. The measurement range for each axis extends from 0 to 4 N. The axial resolution is 6 mN, while the radial resolution is 3.1 mN. At last, temperature compensation was implemented for the sensor environment to mitigate temperature-induced interference, ensuring precise measurements of three-Axis forces. The sensor is expected to be integrated into surgical robots to ensure surgical safety and enhance surgical quality.

关键词： Temperature sensors Temperature measurement Medical robotics Sensitivity Instruments Linearity Robot sensing systems

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Generalized state-feedback controller synthesis for underactuated systems through bayesian optimization

arXiv

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arXiv 2021年

作者： Solis, Miguel A. Thomas, Sinnu Susan Automation and Robotics Department Faculty of Engineering Universidad Andres Bello Santiago Chile Kerala India

Underactuated systems pose the challenge of being able to control a plant whose degrees of freedom are not necessarily directly linked to an actuator or where such a relationship is not straightforward. Rotary inverted pendulum is an example of such systems, which on its simplest representation consists of a pendulum whose vertical angle should be taken up to the upward unstable position based on the impulse given from another bar and an appropriate control strategy, bar that is controlled by an electrical motor. This problem is often tackled by linear control theory with state-feedback controllers that is frequently obtained by means of designing a feedback gain meeting some constraints. This article reports a Bayesian Optimization approach for designing a generalized state-feedback controller, that involves more parameters than a simple state-feedback control law, but with the benefit of achieving lower control effort in terms of the signal amplitude. The source code is made publicly available to facilitate further research. Copyright © 2021, The Authors. All rights reserved.

关键词： Pendulums

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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IEEE International Conference on robotics and Biomimetics

作者： Muyang Hou Zhenya Lei Haidong Hu Zhong Wang Yong Wang Le Xie Hesheng Wang Department of Automation Shanghai Jiao Tong University Shanghai China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Beijing Institute of Control Engineering Beijing China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant; on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A* which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion.

关键词： Hands Trajectory tracking Trajectory planning Service robots Stability analysis Safety Mobile robots Resource management Splines (mathematics) Trajectory optimization

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An Untethered Soft Robotic Gripper with Adjustable Grasping Modes and Force Feedback

An Untethered Soft Robotic Gripper with Adjustable Grasping ...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Yang, Yang Zhu, Honghui Liu, Jia Li, Yingtian Zhou, Jianshu Ren, Tao Ren, Yi School of Automation Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China Jiangsu Province Engineering Research Center of Intelligent Meteorological Exploration Robot China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong Hong Kong Hong Kong Center for Logistics Robotics Hong Kong Hong Kong School of Mechanical and Electrical Engineering Chengdu University of Technology Chengdu610059 China Advanced Manufacturing Lab Huawei Technologies Shenzhen China

ISBN: (纸本)9781665481090

In this paper, we propose a three-finger soft robotic gripper, which adopts an untethered and under-actuated design with simple structure and easy operation. The rotation of two servomotors is used to control the positions of the fingers, which provides the fingers with adjustable grasping modes and improves the adaptation of the gripper to objects with different shapes. A pressure sensor is integrated at the end of the finger to provide force feedback, which is used to detect the contact force when grasping the object and enables the gripper to provide the proper grasping force. The experimental section characterizes the bending of the soft robotic finger, and the gripper is integrated at the end of a collaborative robotic arm to demonstrate its adjustable grasping posture and force feedback function. The soft robotic gripper is expected to be used in a variety of scenarios, such as service robot, food industry or garbage sorting. © 2022 IEEE.

关键词： Grippers

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Intelligent Accident Recognition and Notification System using Hybrid Deep Learning and IoT

Intelligent Accident Recognition and Notification System usi...

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Soft Computing for Security Applications (ICSCSA), International Conference on

作者： P. Sathish Kumar Ramesh Singh Rawat Manish Shrimali Swapnil Parikh Harshal Patil Ramya Maranan Department of Robotics & Automation United Institute of Technology Coimbatore Tamil Nadu India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Computer Science and IT Janardan Rai Nagar Rajasthan Vidyapeeth (Deemed to be University) Udaipur Rajasthan India Department of Computer Science and Engineering Parul Institute of Engineering and Technology Parul University Gujarat India Computer Science and Engineering Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune Maharashtra India Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

ISBN: (数字)9798331515720

ISBN: (纸本)9798331515737

Ensuring the safety of individuals should be a top priority. Everyone wants to return home safely. Many riders continue to disregard safety constraints, increasing the chance of accidents that result in death. It is critical to incorporate the latest technology into road monitoring systems to make cities smarter and to ensure rider safety. For this research, Deep Learning (DL) and the Internet of Things (IoT) were chosen for effective road surveillance and alert systems. The primary goal of the study is to detect and inform riders about accidents that occur along their path and to provide details about the location of the detected accident. Additionally, the system provides the vehicle's speed. To identify automobile accidents in the footage, a hybrid DL model that includes Convolutional Neural Network - Bidirectional Long Short-Term Memory (CNN-Bi-LSTM) is suggested. For the model's training, both accident and non-accident data were collected. The model is evaluated using three metrics: accuracy, loss, and execution time. The next step is to upload the recommended model to the ThingSpeak cloud. A Graphical User Interface (GUI) is being created in the ThingSpeak cloud. The GUI displays the vehicle's speed, accident images, and the precise location of the accident scene using the Raspberry Pi, speed sensor, Pi-camera, and Global Positioning System (GPS) module. An LED is also integrated into the GUI to alert the user. A real-world test is conducted on the designed system. The proposed solution has many advantages and will ensure driver safety.

关键词： Deep learning Training Cloud computing Accuracy Roads Surveillance Feature extraction Safety Accidents Graphical user interfaces

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Prediction and Modeling of Tool Wear with Cutting Force and Fine Gaussian Support Vector Machine in Drilling

Prediction and Modeling of Tool Wear with Cutting Force and ...

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International Virtual Conference on Emerging Trends in Design, Manufacturing, Materials and Thermal Sciences, ETDMMT 2020

作者： Mahendran, G. Sai Balaji, M.A. Susai Mary, J. Dinakaran, D. Department of Mechanical Engineering B S Abdur Rahman Crescent Institute of Science and Technology Chennai India Department of Electronics and Instrumentation Engineering B S Abdur Rahman Crescent Institute of Science and Technology Chennai India Center for Automation and Robotics Hindustan Institute of Technology and Science Chennai India

ISBN: (纸本)9789813364271

The tool wear is a vital problem in machining which affects the accuracy, geometry of the workpiece and also productivity. This paper presents a cutting-force-based monitoring method with a Gaussian Support Vector Machine for tool wear prediction in a drilling process. The experimental results show that the tool wear has a significant effect on the cutting forces. Statistical features in time and frequency domains are extracted from the measured force signals and are used as inputs to the Support Vector Machine (SVM). The machining parameters speed and feed are also taken as inputs for tool wear prediction as they greatly influence the cutting force. The fine Gaussian SVM algorithm is able to model the tool wear with a prediction accuracy of 88% and can be used for online diagnosis of tool wear. The results of the Gaussian SVM algorithm are compared with standard algorithms like ANN to prove its efficiency. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Condition monitoring Fine Gaussian SVM drilling Force Tool wear

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